The invention is in the field of image systems, and is particularly relevant to the field of image feature identification.
In the field of image processing, the term "scanning" refers to the rendering of an image into a string of individual picture elements (pixels), each corresponding to an elemental portion of the image and representing the instantaneous value of an optical attribute of the image at that point. In black and white television, light intensity is the attribute represented by a pixel. In digitized monochromatic imaging systems, a pixel is a multi-bit, digital representation of light intensity. The succession of pixels representing the serialization of an image typically is provided in a standard format composed of lines, fields, and frames.
In color imaging systems, a pixel represents not only the intensity of light at the corresponding point of an image, but also other chromaticity attributes which, when combined with intensity, represent the color of the image point. Scanned color imaging systems are well known in the art, as are a variety of formats for signals representing the chromaticity of image picture elements. Two of the best known standard scanned color image representations are the NTSC and RGB standards.
These standards are based upon one or more representations of color space. When used herein, the term "color space" refers to any one of a number of three-dimensional representations of all of the possible combinations of three predetermined color attributes. These three attributes are referred to hereinafter as "color elements". One set of color elements, for example, includes hue, saturation, and intensity.
Monochromatic (black and white) imaging systems which operate to identify features contained in an image are relatively slow and expensive when compared to the tasks they must perform. Essentially, no single pixel in a monochromatic image is, alone, identifiable as belonging to a particular feature of the image. This is because, with changes in illumination or with shadows, any point on a feature could potentially appear as any brightness to an imager (camera) regardless of the feature's intrinsic color. Typically, a monochromatic imaging system identifies an image feature by detecting the edges of the feature, algorithmically connecting the feature's edges, and then using information representing the connected edges to reconstruct the size and shape of the feature in the image.
In the typical industrial application, a robot system may employ a vision system of which an imaging system is a component. In this regard, a "vision" system is one which enables a robot mechanism to observe an image and to correlate it with a paradigm image, in order to conduct industrial processing of workpieces which come periodically into the vision system's field of view. For example, FIG. 1 represents a workpiece 10 comprising a flat, recessed container for an array of color-coded pills 12-22. The pills 12-22 form a cycle of birth control pills which are meant to be taken in a predetermined sequence. Each pill's position in the sequence is indicated by a particular color. An assembly line which produces packages such as the container 10 will, at some point, inspect each pill package to determine whether the pills have been placed in it in the proper sequence. A vision system employed for this purpose will compare each pill carrier with an exemplary image of a carrier having pills in the proper sequence.
A monochromatic image system would have to enhance and locate the edges of the pills 12-22 of each carrier coming into the view of the vision system, would have to use the edge information to reconstruct the size and shape of the pills in the carrier, and then would compare the size and shape data with the stored exemplary image of a pill carrier to identify the features (the pills) and their locations. This type of image correlation is costly and systems which perform it in a reasonable time are, necessarily, expensive.
When black and white information is insufficient to achieve the desired results, as in the example where the pills must be differentiated on the basis of their colors, additional color information represents a substantial increase in the bandwidth of a vision system.